Power factor correction technique based on artificial neural networks

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dc.contributor.authorSagiroglu S.
dc.contributor.authorColak I.
dc.contributor.authorBayindir R.
dc.date.accessioned2024-07-22T08:23:08Z
dc.date.available2024-07-22T08:23:08Z
dc.date.issued2006
dc.description.abstractThis paper presents a novel technique based on artificial neural networks (ANNs) to correct the line power factor with variable loads. A synchronous motor controlled by the neural compensator was used to handle the reactive power of the system. The ANN compensator was trained with the extended delta-bar-delta learning algorithm. The parameters of the ANN were then inserted into a PIC 16F877 controller to get a better and faster compensation. The results have shown that the proposed novel technique developed in this work overcomes the problems occurring in conventional compensators including over or under compensation, time delay and step changes of reactive power and provides accurate, low cost and fast compensation compared to the technique with capacitor groups. © 2006 Elsevier Ltd. All rights reserved.
dc.identifier.DOI-ID10.1016/j.enconman.2006.02.018
dc.identifier.issn01968904
dc.identifier.urihttp://akademikarsiv.cbu.edu.tr:4000/handle/123456789/19380
dc.language.isoEnglish
dc.subjectCosts
dc.subjectElectric power factor correction
dc.subjectLearning algorithms
dc.subjectParameter estimation
dc.subjectProblem solving
dc.subjectSynchronous motors
dc.subjectDelta-bar-delta learning algorithm
dc.subjectNeural compensators
dc.subjectPower factor correction
dc.subjectNeural networks
dc.titlePower factor correction technique based on artificial neural networks
dc.typeArticle

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